Tadikonda Venkata Bharat

Novel procedure for the estimation of swelling pressures of compacted bentonites based on diffuse double layer theory

Bentonite clays are proven to be attractive as buffer and backfill material in high-level nuclear waste repositories around the world. A quick estimation of swelling pressures of the compacted bentonites for different clay–water–electrolyte interactions is essential in the design of buffer and backfill materials. The theoretical studies on the swelling behavior of bentonites are based on diffuse double layer (DDL) theory. To establish theoretical relationship between void ratio and swelling pressure (e versus P), evaluation of elliptic integral and inverse analysis are unavoidable. In this paper, a novel procedure is presented to establish theoretical relationship of e versus P based on the Gouy–Chapman method. The proposed procedure establishes a unique relationship between electric potentials of interacting and non-interacting diffuse clay–water–electrolyte systems. A procedure is, thus, proposed to deduce the relation between swelling pressures and void ratio from the established relation between electric potentials. This approach is simple and alleviates the need for elliptic integral evaluation and also the inverse analysis. Further, application of the proposed approach to estimate swelling pressures of four compacted bentonites, for example, MX 80, Febex, Montigel and Kunigel V1, at different dry densities, shows that the method is very simple and predicts solutions with very good accuracy. Moreover, the proposed procedure provides continuous distributions of e versus P and thus it is computationally efficient when compared with the existing techniques.

PREDICTION OF COMPRESSIBILITY DATA FOR HIGHLY PLASTIC CLAYS USING DIFFUSE DOUBLE-LAYER THEORY

Montmorillonite-rich clays are important in many engineering applications. The compressibility of such plastic clays at high consolidation pressures is important for predicting routine settlement and for applications in nuclear-waste repositories. Laboratory measurement of compressibility data at high consolidation pressures is not only time consuming but very expensive also. Theoretical predictions can help to determine the compressibility of plastic clays at high consolidation pressures. A linear relationship between e/eNvs. 1/√P (eN is the normalization void ratio at normalization pressure N and P is the consolidation pressure) was derived using diffuse double-layer theory. The compressibility data of several plastic clays in published studies were found to support the derived relationship. A generalized theoretical equation was proposed to predict the compressibility data over a wide range of consolidation pressures using an experimentally measured void ratio at low consolidation pressure. The compressibility data for different plastic clays were predicted accurately up to maximum consolidation pressures that ranged from 0.7 to 30 MPa using an experimentally measured void ratio near the pre-consolidation pressure. The preconsolidation pressures for different clays considered here ranged from 25 to 133 kPa. The proposed predictive model is supported by experimental data, is simple, and does not require knowledge of clay-surface and pore-fluid parameters.

Robust solver based on modified particle swarm optimization for improved solution of diffusion transport through containment facilities

Accurate estimation of mass transport parameters is necessary for overall design and evaluation processes of the waste disposal facilities. The mass transport parameters, such as effective diffusion coefficient, retardation factor and diffusion accessible porosity, are estimated from observed diffusion data by inverse analysis. Recently, particle swarm optimization (PSO) algorithm has been used to develop inverse model for estimating these parameters that alleviated existing limitations in the inverse analysis. However, PSO solver yields different solutions in successive runs because of the stochastic nature of the algorithm and also because of the presence of multiple optimum solutions. Thus the estimated mean solution from independent runs is significantly different from the best solution. In this paper, two variants of the PSO algorithms are proposed to improve the performance of the inverse analysis. The proposed algorithms use perturbation equation for the gbest particle to gain information around gbest region on the search space and catfish particles in alternative iterations to improve exploration capabilities. Performance comparison of developed solvers on synthetic test data for two different diffusion problems reveals that one of the proposed solvers, CPPSO, significantly improves overall performance with improved best, worst and mean fitness values. The developed solver is further used to estimate transport parameters from 12 sets of experimentally observed diffusion data obtained from three diffusion problems and compared with published values from the literature. The proposed solver is quick, simple and robust on different diffusion problems.

Accurate parameter estimation of contaminant transport inverse problem using particle swarm optimization

Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

Agents based algorithms for design parameter estimation in contaminant transport inverse problems

A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigenvalues obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigenvalues from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigenvalues are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.

A CRITICAL APPRAISAL OF DEBYE LENGTH IN CLAY-ELECTROLYTE SYSTEMS

The equivalent diffuse double layer (DDL) thickness in clay-electrolyte systems is a very useful parameter for analyzing the engineering behavior of clays under different environmental conditions. The equivalent DDL thickness is generally assumed to be equal to the characteristic (Debye) length. The present work examined critically the applicability of characteristic length to define equivalent DDL thickness under various clay-surface and pore-fluid conditions. A critical analysis is presented of the changes in the equivalent DDL thickness and characteristic length under the influence of different clay-surface and electrolyte properties. The equivalent DDL thickness was found to be smaller than the characteristic length for a wide range of surface and pore-fluid parameters normally encountered in engineering practice. An accurate and simple power relationship was developed to predict the equivalent DDL thickness from the characteristic length, which is applicable to a wide range of clay-electrolyte systems.

Specific ion effects on surrogate compatibility indices of bentonite for hydraulic barrier applications

Abstract Bentonites are extensively used in waste containment facilities for controlling the migration of contaminants. The performance assessment of these facilities requires study on long-term hydraulic behaviour of proposed barrier material in the presence of different salts. Liquid limit water content and equilibrium sediment volume (ESV) of clays in the presence of different salt electrolytes are recognised to be the surrogate compatibility indices for understanding the long-term hydraulic behaviour of bentonites. The present paper provided a detailed analysis of influencing parameters on the behaviour of potential clay barrier through these two surrogate compatibility tests. The influence of different pore-fluid parameters, such as electrolyte concentration and specific ion effects on the behaviour of Indian bentonite was presented. The controlling mechanism of these two indices in the presence of different pore-fluid parameters was brought out. A relationship was obtained between the liquid limit water content and ESV data from the present study and the literature studies on different clays. Similarly, a good correlation was found between these indices and equilibrium hydraulic conductivity in the presence of different salt concentrations and different hydrated cation radii.

Inverse modeling in geoenvironmental engineering using a novel particle swarm optimization algorithm

Algorithms derived by mimicking the nature are extremely useful for solving many real world problems in different engineering disciplines. Particle swarm optimization (PSO) especially has been greatly acknowledged for its simplicity and efficiency in obtaining good solutions for complex problems. However, premature convergence of the standard PSO and many of its variants is a downside particularly for its application to the inverse problems. This aspect encourages further research in developing efficient algorithms for such problems. In this work, a novel PSO algorithm is proposed by introducing fitness of a new location in the search space into the standard PSO which enables to enhance the success rate of the algorithm. The proposed algorithm uses center of mass of the population to compare the fitness of global best particle in each iteration. The proposed algorithm is applied to solve contaminant transport inverse problem. The performance of different PSO algorithms is compared on synthetic test data and it is shown that the proposed algorithm outperforms its counterparts. Further, accurate design parameters are estimated using the proposed inverse model from the experimental data.

Numerical modeling of the contaminant Transport through stratified soil

The transport processes of the dissolved chemicals in stratified or layered soils have been studied for several decades. In case of the solute transport through stratified layers, interface condition plays an important role in determining appropriate transport parameters. First‐ type and third‐ type interface conditions are generally used in the literature. A first‐type interface condition will result in a continuous concentration profile across the interface at the expense of solute mass balance. On the other hand, a discontinuity in concentration develops when a third‐ type interface condition is used. To overcome this problem, a combined first‐ and third‐ type condition at the interface has been widely employed which yields second‐ type condition. This results in a similar break‐through curve irrespective of the layering order, which is non‐physical. In this work, an interface condition is proposed which satisfies the mass balance implicitly and brings the distinction between the breakthrough curves for different layering sequence corroborating with the experimental observations. This is in disagreement with the earlier work by H. M. Selim and co‐workers but, well agreement with the hypothetical result by Bosma and van der Zee; and Van der Zee.

Experimental Analysis of Salt Diffusion in Compacted Clays by Through-Diffusion and Half Cell Technique

The estimation of the model parameters namely effective diffusion coefficient and retardation factor of a potential landfill liner material was presented in this paper using the experimentally measured salt concentration data. Experimental data of concentration variation of time and spatial distance in compacted bentonite was obtained using two diffusion measurement techniques viz. through-diffusion and half cell technique, respectively. The bentonite was subjected to the same concentration gradient and compacted density in both the experimental methods to compare the results and understand underlying mechanism in the diffusion tests. The measured data from the laboratory diffusion techniques was analysed using a Graphical User Interface (GUI)-based Dot-net application CONTRADIS. The CONTRADIS was used to estimate the model parameters by the inverse analysis. The application uses the solution of the forward analysis and stochastic algorithm for the inverse analysis. The retardation factor obtained theoretically was validated using laboratory batch sorption tests.